In the coming year, the expository paper will be completed, and attention will shift to problem areas of Validity of compartmental analysis and uncertainty bounds in analysis of data. One such question is the following. Human in vivo studies are constrained by the amount of blood and number of samples that may be taken. There is need to understand the optimal spacing of these samples in time during the study, and the associated optimal sample sizes. A second question of interest in the following. Disappearance curves, e.g. the glucose disappearance, look like a mixture of exponential decay curves with different rates and positive coefficients. The data consists typically of a modest number of points on these curves. "Curve-stripping" is correspondingly a heuristic technique for fitting the curve optimally to a finite mixture of decay rates (say, e.g., 3 such). For many disappearance curves the curve-stripping is spurious in that the number of components present is unclear at best, and evidence for there being a finite number of such components unconvincing. The circulatory model provides a more natural framework for discussing the structure of these disappearance curves. Recent research has indicated that diffusion and loss in the interstitial fluid combined with circulation provide mathematical curves, identical in appearance to observed disappearance curves. It is hoped that further progress in this direction will permit quantification of diffusion and loss parameters and shed light thereby on interstitial ration.